Honeywell International Inc.

Ademco Inc.

General Electric Company

Purnaprajna Raghavendra Mangsuli

Soumitri N Kolavennu

Pradeep Shetty

Keith L Curtner

Paul C Wacker

Wendy K Foslien

Ondrej Holub

Ranganathan Srinivasan

Wendy Foslien Graber

Harry Kirk Mathews, Jr

Paul Kenneth Houpt

David So Keung Chan

Manthram Sivasubramaniam

Ramprasad Yelchuru

Sunil Shirish Shah

Venkateswaran Narayanan

Pradyumna Sampath

Raj Mohan Bharadwaj

Systems and methods for training a control panel to recognize user defined and preprogrammed sound patterns are provided. Such systems and methods can include the control panel operating in a learning mode, receiving initial ambient audio from a region, and saving the initial ambient audio as an audio pattern in a memory device of the control panel. Such systems and methods can also include the control panel operating in an active mode, receiving subsequent ambient audio from the region, using an audio classification model to make an initial determination as to whether the subsequent ambient audio matches or is otherwise consistent with the audio pattern, determining whether the initial determination is correct, and when the control panel determines that the initial determination is incorrect, modifying or updating the audio classification model for improving the accuracy in detecting future consistency with the audio pattern.

Systems and methods for training devices to recognize sound patterns

Heating, ventilation, and air conditioning (HVAC) controllers are described herein. One method includes receiving an approximate relationship between each of a number of controlled and manipulated variables of an HVAC system, designating one of the number of controlled variables as a primary controlled variable, determining operating parameters for each of the number of manipulated variables that maintain the primary controlled variable based, at least in part, on the approximate relationship between the primary controlled variable and each respective manipulated variable, and determining operating parameters for each of the number of manipulated variables that maintain each of the other controlled variables based, at least in part, on the approximate relationship between each respective other controlled variable and each respective manipulated variable and the determined operating parameters for each of the number of manipulated variables that maintain the primary controlled variable.

Heating, ventilation, and air conditioning system controller

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

System and method for optimal load and source scheduling in context aware homes

Systems and methods for managing a programmable thermostat are described herein. One or more system embodiments include a programmable thermostat having a first management profile; a data acquisition subsystem; and a data analysis subsystem. The data acquisition subsystem is configured to receive thermostat data from the programmable thermostat, and the data analysis subsystem is configured to receive the thermostat data from the data acquisition subsystem, and determine a second management profile for the programmable thermostat based, at least in part, on the thermostat data.

Systems and methods for managing a programmable thermostat

Heating, ventilation, and air conditioning (HVAC) system controllers are described herein. One HVAC controller includes a user interface configured to receive an indication of whether there is a positive or negative relationship between each of a number of controlled variables of an HVAC system and each of a number of manipulated variables of the HVAC system, a memory, and a processor configured to execute executable instructions stored in the memory to determine operating parameters for each of the number of manipulated variables, wherein the determined operating parameters are determined based, at least in part, on whether there is a positive or negative relationship between each respective controlled variable and each respective manipulated variable, and the determined operating parameters are not based on system dynamics and disturbances associated with the HVAC system. The determined operating parameters may be optimal with respect to the current condition of the HVAC system.

A system for disaggregating a gross energy measurement into individual component energy consumption. A collection of components may be situated in a facility. A sensor may obtain electrical signals from one or more power input lines which convey power to the facility for the components. The signals may indicate the total energy consumption by the collection of components. Approaches and/or mechanisms may be used to disaggregate the indication of total energy consumption into indications of individual energy consumption by the components without the need for separately determining the individual energy consumption with additional measurements or instrumentation. Also, approaches and/or mechanisms may be used for integrating a known load activity with whole facility energy consumption for enhancing the component disaggregation. Indications of individual energy consumption permit a reasonable evaluation of components from efficiency, conservation and/or other perspectives.

Energy consumption disaggregation system

An apparatus for controlling a plurality of locomotives, the locomotives being responsive to a plurality of discrete actual commands, the apparatus comprising: a combination generator adapted for generating combinations of the discrete actual commands to yield a command combination set; a performance calculator adapted for calculating a performance parameter set from the command combination set; a feasible combination selector adapted for selecting a feasible combination subset from the command combination set as a function of a discrete performance setpoint, a performance tolerance, and the performance parameter set; an objective function calculator adapted for calculating an objective function set from the feasible combination subset; and an optimal command selector adapted for selecting an optimal command combination from the feasible combination subset corresponding to an optimum value of the objective function set.

Growing community of inventors

Bengaluru, India

Purnaprajna Raghavendra Mangsuli